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Filtros : "Neural Computing and Applications" "Pessin, Gustavo" Limpar

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  • Artigo de periodico

    Toward an emotion efficient architecture based on the sound spectrum from the voice of Portuguese speakers (2024)

    Rocha Filho, Geraldo Pereira ; Meneguette, Rodolfo Ipolito ; Mendonça, Fabio Lucio Lopes de ; Enamoto, Liriam Michi ; Pessin, Gustavo ; Gonçalves, Vinicius Pereira

    Fonte: Neural Computing and Applications. Unidade: ICMC

    Assuntos: EMOÇÕES, VOZ, REDES NEURAIS, RECONHECIMENTO DE VOZ

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    • ABNT

      ROCHA FILHO, Geraldo Pereira et al. Toward an emotion efficient architecture based on the sound spectrum from the voice of Portuguese speakers. Neural Computing and Applications, v. 36, p. 19939–19950, 2024Tradução . . Disponível em: https://doi.org/10.1007/s00521-024-10249-4. Acesso em: 15 nov. 2025.

    • APA

      Rocha Filho, G. P., Meneguette, R. I., Mendonça, F. L. L. de, Enamoto, L. M., Pessin, G., & Gonçalves, V. P. (2024). Toward an emotion efficient architecture based on the sound spectrum from the voice of Portuguese speakers. Neural Computing and Applications, 36, 19939–19950. doi:10.1007/s00521-024-10249-4

    • NLM

      Rocha Filho GP, Meneguette RI, Mendonça FLL de, Enamoto LM, Pessin G, Gonçalves VP. Toward an emotion efficient architecture based on the sound spectrum from the voice of Portuguese speakers [Internet]. Neural Computing and Applications. 2024 ; 36 19939–19950.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1007/s00521-024-10249-4

    • Vancouver

      Rocha Filho GP, Meneguette RI, Mendonça FLL de, Enamoto LM, Pessin G, Gonçalves VP. Toward an emotion efficient architecture based on the sound spectrum from the voice of Portuguese speakers [Internet]. Neural Computing and Applications. 2024 ; 36 19939–19950.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1007/s00521-024-10249-4

  • Artigo de periodico

    Improving the accuracy of a flood forecasting model by means of machine learning and chaos theory: a case study involving a real wireless sensor network deployment in Brazil (2016)

    Furquim, Gustavo; Pessin, Gustavo; Faiçal, Bruno S; Mendiondo, Eduardo Mario ; Ueyama, Jó

    Fonte: Neural Computing and Applications. Unidades: EESC, ICMC

    Assuntos: SISTEMAS DISTRIBUÍDOS, PROGRAMAÇÃO CONCORRENTE

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    • ABNT

      FURQUIM, Gustavo et al. Improving the accuracy of a flood forecasting model by means of machine learning and chaos theory: a case study involving a real wireless sensor network deployment in Brazil. Neural Computing and Applications, v. 27, p. 1129-1141, 2016Tradução . . Disponível em: https://doi.org/10.1007/s00521-015-1930-z. Acesso em: 15 nov. 2025.

    • APA

      Furquim, G., Pessin, G., Faiçal, B. S., Mendiondo, E. M., & Ueyama, J. (2016). Improving the accuracy of a flood forecasting model by means of machine learning and chaos theory: a case study involving a real wireless sensor network deployment in Brazil. Neural Computing and Applications, 27, 1129-1141. doi:10.1007/s00521-015-1930-z

    • NLM

      Furquim G, Pessin G, Faiçal BS, Mendiondo EM, Ueyama J. Improving the accuracy of a flood forecasting model by means of machine learning and chaos theory: a case study involving a real wireless sensor network deployment in Brazil [Internet]. Neural Computing and Applications. 2016 ; 27 1129-1141.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1007/s00521-015-1930-z

    • Vancouver

      Furquim G, Pessin G, Faiçal BS, Mendiondo EM, Ueyama J. Improving the accuracy of a flood forecasting model by means of machine learning and chaos theory: a case study involving a real wireless sensor network deployment in Brazil [Internet]. Neural Computing and Applications. 2016 ; 27 1129-1141.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1007/s00521-015-1930-z
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